1. Field of the Invention:
This invention relates to a method and system for automated classification of distinction between normal lungs and abnormal lungs with interstitial disease in digital chest x-rays.
2. Discussion of Background:
In copending parent application Ser. No. 07/081,143 there is described in detail the prior efforts by researchers in the field of automated techniques in diagnostic radiology. In this parent application there is also disclosed and claimed an automated method for detecting and characterizing interstitial lung diseases based on physical measures of lung texture in digital chest radiographs. As described in Ser. No. 07/081,143, approximately twenty square regions of interest (ROIs) are selected from inter-rib spaces by an automated or manual method, and the non-uniform background trend in each ROI is corrected in order to isolate the overall gross lung anatomy from the underlying fine texture which relates to interstitial disease. After the power spectrum of the lung texture is filtered by the visual system response of the human observer, the rms variation and the first moment of the power spectrum are determined as quantitative texture measures of the magnitude and coarseness (or fineness) of the lung texture, respectively. The present invention builds on that disclosed in Ser. No. 081,143 in that the inventor have determined these texture measures for 100 normal lungs and for 100 abnormal lungs with nodular, reticular, and honeycomb patterns, in order to establish a data base. This data base is then used according to the present invention to establish criteria for automated classification of distinction between normal lungs and abnormal lungs with interstitial disease.